• Title, Summary, Keyword: 혼잡예측

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Network Routing by Traffic Prediction on Time Series Models (시계열 모형의 트래픽 예측에 기반한 네트워크 라우팅)

  • Jung, Sang-Joon;Chung, Youn-Ky;Kim, Chong-Gun
    • Journal of KIISE:Information Networking
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    • v.32 no.4
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    • pp.433-442
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    • 2005
  • An increase In traffic has a large Influence on the performance of a total network. Therefore, traffic management has become an important issue of network management. In this paper, we propose a new routing algorithm that attempts to analyze network conditions using time series prediction models and to propose predictive optimal routing decisions. Traffic congestion is assumed when the predicting result is bigger than the permitted bandwidth. By collecting traffic in real network, the predictable model is obtained when it minimizes statistical errors. In order to predict network traffic based on time series models, we assume that models satisfy a stationary assumption. The stationary assumption can be evaluated by using ACF(Auto Correlation Function) and PACF(Partial Auto Correlation Function). We can obtain the result of these two functions when it satisfies the stationary assumption. We modify routing oaths by predicting traffic in order to avoid traffic congestion through experiments. As a result, Predicting traffic and balancing load by modifying paths allows us to avoid path congestion and increase network performance.

Emprical Tests of Braess Paradox (The Case of Namsan 2nd Tunnel Shutdown) (브라이스역설에 대한 실증적 검증 (남산2호터널 폐쇄사례를 중심으로))

  • 엄진기;황기연;김익기
    • Journal of Korean Society of Transportation
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    • v.17 no.3
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    • pp.61-70
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    • 1999
  • The Purpose of this study is to test whether Braess Paradox (BP) can be revealed in a real world network. Fer the study, Namsan 2nd tunnel case is chosen, which was shut down for 3 years for repair works. The revelation of BP is determined by analyzing network-wise traffic impacts followed by the tunnel closure. The analysis is conducted using a network simulation model called SECOMM developed for the congestion management of the Seoul metropolitan area. Also, the existence of BP is further identified by a before-after traffic survey result of the major arterials nearby the Namsan 2nd tunnel. The model estimation expected that the closure of Namsan 2nd tunnel improve the network-wise average traffic speed from 21.95km/h to 22.21km/h when the travel demand in the study area and congestion Pricing scheme on Namsan 1st & 3rd tunnels remain unchanged. In addition, the real world monitoring results of the corridors surrounding Namsan 2nd tunnel show that the average speed increases from 29.53km/h to 30.37km/h after the closure. These findings clearly identify the BP Phenomenon is revealed in this case.

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An Active Queue Management Method Based on the Input Traffic Rate Prediction for Internet Congestion Avoidance (인터넷 혼잡 예방을 위한 입력율 예측 기반 동적 큐 관리 기법)

  • Park, Jae-Sung;Yoon, Hyun-Goo
    • 전자공학회논문지 IE
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    • v.43 no.3
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    • pp.41-48
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    • 2006
  • In this paper, we propose a new active queue management (AQM) scheme by utilizing the predictability of the Internet traffic. The proposed scheme predicts future traffic input rate by using the auto-regressive (AR) time series model and determines the future congestion level by comparing the predicted input rate with the service rate. If the congestion is expected, the packet drop probability is dynamically adjusted to avoid the anticipated congestion level. Unlike the previous AQM schemes which use the queue length variation as the congestion measure, the proposed scheme uses the variation of the traffic input rate as the congestion measure. By predicting the network congestion level, the proposed scheme can adapt more rapidly to the changing network condition and stabilize the average queue length and its variation even if the traffic input level varies widely. Through ns-2 simulation study in varying network environments, we compare the performance among RED, Adaptive RED (ARED), REM, Predicted AQM (PAQM) and the proposed scheme in terms of average queue length and packet drop rate, and show that the proposed scheme is more adaptive to the varying network conditions and has shorter response time.

A Performance Improvement Method with Considering of Congestion Prediction and Packet Loss on UDT Environment (UDT 환경에서 혼잡상황 예측 및 패킷손실을 고려한 성능향상 기법)

  • Park, Jong-Seon;Lee, Seung-Ah;Kim, Seung-Hae;Cho, Gi-Hwan
    • The Journal of the Korea Contents Association
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    • v.11 no.2
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    • pp.69-78
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    • 2011
  • Recently, the bandwidth available to an end user has been dramatically increasing with the advancing of network technologies. This high-speed network naturally requires faster and/or stable data transmission techniques. The UDT(UDP based Data Transfer protocol) is a UDP based transport protocol, and shows more efficient throughput than TCP in the long RTT environment, with benefit of rate control for a SYN time. With a NAK event, however, it is difficult to expect an optimum performance due to the increase of fixed sendInterval and the flow control based on the previous RTT. This paper proposes a rate control method on following a NAK, by adjusting the sendInterval according to some degree of RTT period which calculated from a set of experimental results. In addition, it suggests an improved flow control method based on the TCP vegas, in order to predict the network congestion afterward. An experimental results show that the revised flow control method improves UDT's throughput about 20Mbps. With combining the rate control and flow control proposed, the UDT throughput can be improved up to 26Mbps in average.

On the efficient buffer management and early congestion detection at a Internet gateway based on the TCP flow control mechanism (TCP 흐름제어를 이용한 인터넷 게이트웨이에서의 예측기반 버퍼관리 및 조기혼잡예측기법)

  • Yeo Jae-Yung;Choe Jin-Woo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.1B
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    • pp.29-40
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    • 2004
  • In this paper, we propose a new early congestion detection and notification technique called QR-AQM. Unlike RED and it's variation, QR-AQM measures the total traffic rate from TCP sessions, predicts future network congestion, and determine the packet marking probability based on the measured traffic rate. By incorporating the traffic rate in the decision process of the packet marking probability, QR-AQM is capable of foreseeing future network congestion as well as terminating congestion resolution procedure in much more timely fashion than RED. As a result, simulation results show that QR-AQM maintains the buffer level within a fairly narrow range around a target buffer level that may be selected arbitrarily as a control parameter. Consequently, compared to RED and its variations, QR-AQM is expected to significantly reduce the jitter and delay variance of packets traveling through the buffer while achieving nearly identical link utilization.

Defining Rail Transit Level of Service and Analysis of it's Affection According to Rapid Transit Railway(KTX) (고속철도(KTX) 수요에 따른 dwelling time예측 모형개발)

  • Suh, Sun-Duck;Shin, Young-Ho;Shim, Hyun-Jin;Kim, Hwan-Su
    • Proceedings of the KSR Conference
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    • pp.1612-1627
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    • 2008
  • Dwelling time is one of the factors that influence in rail. Current research in dwelling time has been focusing on railways, the state of the research in high-speed rail's dwelling time is not complete. Dwelling time is consisted of time to open door, time to get into and out of vehicle and time of the departure it takes after the passenger's door was closed, it was affected by various factors such as congestion's degree in vehicle, the number of persons that get into and out of vehicle, congestion's degree in station. In order to analyze theses, we need data analysis such as the number of persons that get into and out of vehicle, congestion's degree in station, congestion's degree in vehicle, but the congestion's degree and passenger's distribution chart in vehicle is excluded in this research due to difficulty of gathering data, and thus we will develop forecasting models through high-speed rail's demand most affected by the dwelling time.

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A Study on Predictive Traffic Information Using Cloud Route Search (클라우드 경로탐색을 이용한 미래 교통정보 예측 방법)

  • Jun Hyun, Kim;Kee Wook, Kwon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.287-296
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    • 2015
  • Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.

A New RED Algorithm Adapting Automatically in Various Network Conditions (다양한 네트워크 환경에 자동적으로 적응하는 RED 알고리즘)

  • Kim, Dong-Choon
    • The Journal of Advanced Navigation Technology
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    • v.18 no.5
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    • pp.461-467
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    • 2014
  • Active queue management (AQM) algorithms run on routers and detect incipient congestion by typically monitoring the instantaneous or average queue size. When the average queue size exceeds a certain threshold, AQM algorithms infer congestion on the link and notify the end systems to back off by proactively dropping some of the packets arriving at a router or marking the packets to reduce transmission rate at the sender. Among the existing AQM algorithms, random early detection (RED) is well known as the representative queue-based management scheme by randomizing packet dropping. To reduce the number of timeouts in TCP and queuing delay, maintain high link utilization, and remove bursty traffic biases, the RED considers an average queue size as a degree of congestions. However, RED do not well in the specified networks conditions due to the fixed parameters($P_{max}$ and $TH_{min}$) of RED. This paper addresses a extended RED to be adapted in various networks conditions. By sensing network state, $P_{max}$ and $TH_{min}$ can be automatically changed to proper value and then RED do well in various networks conditions.

Development of the Train Dwell Time Model : Metering Strategy to Control Passenger Flows in the Congested Platform (승강장 혼잡관리를 위한 열차의 정차시간 예측모형)

  • KIM, Hyun;Lee, Seon-Ha;LIM, Guk-Hyun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.3
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    • pp.15-27
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    • 2017
  • In general, increasing train dwell time leads to increasing train service frequency, and it in turn contributes to increasing the congestion level of train and platform. Therefore, the studies on train dwell time have received growing attention in the perspective of scheduling train operation. This study develops a prediction model of train dwell time to enable train operators to mitigate platform congestion by metering passenger inflow at platform gate with respect to platform congestion levels in real-time. To estimate the prediction model, three types of independent variables were applied: number of passengers to get into train, number of passengers to get out of trains, and train weights, which are collectable in real-time. The explanatory power of the estimated model was 0.809, and all of the dependent variables were statistically significant at the 99%. As a result, this model can be available for the basis of on-time train service through platform gate metering, which is a strategy to manage passenger inflow at the platform.

Improvement of Service Quality for Urban Railway Operations Using Simulation (시뮬레이션을 이용한 도시철도 운행 서비스품질 개선에 관한 연구)

  • Kim, DongHee;Lee, HongSeob
    • Journal of the Korean Society for Railway
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    • v.20 no.1
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    • pp.156-163
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    • 2017
  • In the major operation sections of the urban railway, there has been habitual delay, and delay propagation; another problem is the increase of crowds and of inconvenience to passengers. The urban railway has different characteristics from rural railways, such as uncertainty of demand and irregularity of train operation. In urban railways, recently, operators manage quality indicators of service using operation results, such as the delay of train operation and the congestion of trains. However, because the urban railway has characteristics in which demand, passenger behavior, and train operation mutually affect each other, it is difficult to express the quality of service that passengers actually feel. In this paper, we suggest a quality indicator of service from the viewpoint of passengers, and present a demand responsive multi-train simulation method to predict dynamic dwell time and train operation status; we also use simulation results to consider changes in the quality indicator of service.